ICALEPCS2019 - List of Authors (Salvachua, B.)

Paper	Title	Page
MOCPL04	Software Architecture for Automatic LHC Collimator Alignment Using Machine Learning	78
	G. Azzopardi, S. Redaelli, B. Salvachua CERN, Geneva, Switzerland A. Muscat, G. Valentino University of Malta, Information and Communication Technology, Msida, Malta
	The Large Hadron Collider at CERN relies on a collimation system to absorb unavoidable beam losses before they reach the superconducting magnets. The collimators are positioned close to the beam in a transverse setting hierarchy achieved by aligning each collimator with a precision of a few tens of micrometers. In previous years, collimator alignments were performed semi-automatically, requiring collimation experts to be present to oversee and control the entire process. In 2018, manual, expert control of the alignment procedure was replaced by dedicated machine learning algorithms, and this new software was used for collimator alignments throughout the year. This paper gives an overview of the software re-design required to achieve fully automatic collimator alignments, describing in detail the software architecture and controls systems involved. Following this successful deployment, this software will be used in the future as the default alignment software for the LHC. G. Valentino et al., "Semi-automatic beam-based LHC collimator alignment", Physical Review Special Topics-Accelerators and Beams vol. 15, no. 5, 2012.
	Slides MOCPL04 [5.933 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-MOCPL04
About •	paper received ※ 28 September 2019 paper accepted ※ 09 October 2019 issue date ※ 30 August 2020
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

MOPHA010	Automatic Beam Loss Threshold Selection for LHC Collimator Alignment	208
	G. Azzopardi, S. Redaelli, B. Salvachua CERN, Geneva, Switzerland A. Muscat, G. Valentino University of Malta, Information and Communication Technology, Msida, Malta
	The collimation system used in the Large Hadron Collider at CERN is positioned around the beam with a hierarchy that protects sensitive equipment from unavoidable beam losses. The collimator settings are determined using a beam-based alignment technique, where collimator jaws are moved towards the beam until the beam losses exceed a predefined threshold. This threshold needs to be updated dynamically, corresponding to the changes in the beam losses. The current method for aligning collimators is semi-automated requiring a collimation expert to monitor the loss signals and continuously select and update the threshold accordingly. The human element in this procedure is a major bottleneck for speeding up the alignment. This paper therefore proposes a method to fully automate this threshold selection. A data set was formed from previous alignment campaigns and analyzed to define an algorithm that produced results consistent with the user selections. In over 90% of the cases the difference between the two was negligible and the algorithm presented in this study was used for collimator alignments throughout 2018.
	Poster MOPHA010 [1.763 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-MOPHA010
About •	paper received ※ 28 September 2019 paper accepted ※ 08 October 2019 issue date ※ 30 August 2020
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

MOPHA064	An Off-Momentum Beam Loss Feedback Controller and Graphical User Interface for the LHC	360
	B. Salvachua, D. Alves, G. Azzopardi, S. Jackson, D. Mirarchi, M. Pojer CERN, Geneva, Switzerland G. Valentino University of Malta, Information and Communication Technology, Msida, Malta
	During LHC operation, a campaign to validate the configuration of the LHC collimation system is conducted every few months. This is performed by means of loss maps, where specific beam losses are deliberately generated with the resulting loss patterns compared to expectations. The LHC collimators have to protect the machine from both betatron and off-momentum losses. In order to validate the off-momentum protection, beam losses are generated by shifting the RF frequency using a low intensity beam. This is a delicate process that, in the past, often led to the beam being dumped due to excessive losses. To avoid this, a feedback system based on the 100 Hz data stream from the LHC Beam Loss system has been implemented. When given a target RF frequency, the feedback system approaches this frequency in steps while monitoring the losses until the selected loss pattern conditions are reached, so avoiding the excessive losses that lead to a beam dump. This paper will describe the LHC off-momentum beam loss feedback system and the results achieved.
	Poster MOPHA064 [5.005 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-MOPHA064
About •	paper received ※ 27 September 2019 paper accepted ※ 10 October 2019 issue date ※ 30 August 2020
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Page

Software Architecture for Automatic LHC Collimator Alignment Using Machine Learning

78

G. Azzopardi, S. Redaelli, B. Salvachua
CERN, Geneva, Switzerland
A. Muscat, G. Valentino
University of Malta, Information and Communication Technology, Msida, Malta

The Large Hadron Collider at CERN relies on a collimation system to absorb unavoidable beam losses before they reach the superconducting magnets. The collimators are positioned close to the beam in a transverse setting hierarchy achieved by aligning each collimator with a precision of a few tens of micrometers. In previous years, collimator alignments were performed semi-automatically*, requiring collimation experts to be present to oversee and control the entire process. In 2018, manual, expert control of the alignment procedure was replaced by dedicated machine learning algorithms, and this new software was used for collimator alignments throughout the year. This paper gives an overview of the software re-design required to achieve fully automatic collimator alignments, describing in detail the software architecture and controls systems involved. Following this successful deployment, this software will be used in the future as the default alignment software for the LHC.
*G. Valentino et al., "Semi-automatic beam-based LHC collimator alignment", Physical Review Special Topics-Accelerators and Beams vol. 15, no. 5, 2012.

Slides MOCPL04 [5.933 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-MOCPL04

About •

paper received ※ 28 September 2019 paper accepted ※ 09 October 2019 issue date ※ 30 August 2020

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

MOPHA010

Automatic Beam Loss Threshold Selection for LHC Collimator Alignment

208

G. Azzopardi, S. Redaelli, B. Salvachua
CERN, Geneva, Switzerland
A. Muscat, G. Valentino
University of Malta, Information and Communication Technology, Msida, Malta

The collimation system used in the Large Hadron Collider at CERN is positioned around the beam with a hierarchy that protects sensitive equipment from unavoidable beam losses. The collimator settings are determined using a beam-based alignment technique, where collimator jaws are moved towards the beam until the beam losses exceed a predefined threshold. This threshold needs to be updated dynamically, corresponding to the changes in the beam losses. The current method for aligning collimators is semi-automated requiring a collimation expert to monitor the loss signals and continuously select and update the threshold accordingly. The human element in this procedure is a major bottleneck for speeding up the alignment. This paper therefore proposes a method to fully automate this threshold selection. A data set was formed from previous alignment campaigns and analyzed to define an algorithm that produced results consistent with the user selections. In over 90% of the cases the difference between the two was negligible and the algorithm presented in this study was used for collimator alignments throughout 2018.

Poster MOPHA010 [1.763 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-MOPHA010

About •

paper received ※ 28 September 2019 paper accepted ※ 08 October 2019 issue date ※ 30 August 2020

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

MOPHA064

An Off-Momentum Beam Loss Feedback Controller and Graphical User Interface for the LHC

360

B. Salvachua, D. Alves, G. Azzopardi, S. Jackson, D. Mirarchi, M. Pojer
CERN, Geneva, Switzerland
G. Valentino
University of Malta, Information and Communication Technology, Msida, Malta

During LHC operation, a campaign to validate the configuration of the LHC collimation system is conducted every few months. This is performed by means of loss maps, where specific beam losses are deliberately generated with the resulting loss patterns compared to expectations. The LHC collimators have to protect the machine from both betatron and off-momentum losses. In order to validate the off-momentum protection, beam losses are generated by shifting the RF frequency using a low intensity beam. This is a delicate process that, in the past, often led to the beam being dumped due to excessive losses. To avoid this, a feedback system based on the 100 Hz data stream from the LHC Beam Loss system has been implemented. When given a target RF frequency, the feedback system approaches this frequency in steps while monitoring the losses until the selected loss pattern conditions are reached, so avoiding the excessive losses that lead to a beam dump. This paper will describe the LHC off-momentum beam loss feedback system and the results achieved.

Poster MOPHA064 [5.005 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-MOPHA064

About •

paper received ※ 27 September 2019 paper accepted ※ 10 October 2019 issue date ※ 30 August 2020

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)